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The 69 Controversies of AI Adoption Is Now Available on Amazon
The 69 Controversies of AI Adoption by S. M. Sohn brings up a wide range of controversial topics related to AI adoption, to help readers imagine what AI may bring to our future and examine the realm of possibilities.
//t.co/h3VMvgKqRh
Introduction to Book
We may think of controversies related to AI as either about the forecast, or predictions of what is going to happen, and about the decisions, or what kinds of actions we should take.
Forecast: How soon will we reach AGI? How intelligent will AI become? Will ASI be friendly to humanity?
Decision: Should we accelerate or decelerate the development of AGI? Should we ban development of AGI?
The organization of the controversies takes its inspiration from the Korean flag, which may be thought of as the map of the universe. The number “69” represents the accelerating and decelerating forces in AI, and takes from the center circle of the Korean flag. People may be familiar with this concept as “Eum” (decelerating) and “Yang” (accelerating), where two opposing forces balance each other.
Examples of the Center of Controversies:
Accelerating Force: development in AI technology
Decelerating Force: regulations to mitigate AI risks
The controversies are organized into 8 directions, which take from the outer bars of the Korean flag design. The hope is that this organization will help readers find the areas they are interested in.
1. AI and Individuals
2. AI and Family
3. AI and Businesses
4. AI and Society
5. AI and Economy
6. AI and Government
7. AI and the World
8. AI and the Universe
If the goal of The Last AI was to help people share their ideas with common vocabulary, the goal of this book is to help readers develop their own views and own strategies to prepare the future.
In this sense, this is a book that raises more questions than we can answer.
The 69 Controversies of AI Adoption by S. M. Sohn brings up a wide range of controversial topics related to AI adoption, to help readers imagine what AI may bring to our future and examine the realm of possibilities.
//t.co/h3VMvgKqRh
Introduction to Book
We may think of controversies related to AI as either about the forecast, or predictions of what is going to happen, and about the decisions, or what kinds of actions we should take.
Forecast: How soon will we reach AGI? How intelligent will AI become? Will ASI be friendly to humanity?
Decision: Should we accelerate or decelerate the development of AGI? Should we ban development of AGI?
The organization of the controversies takes its inspiration from the Korean flag, which may be thought of as the map of the universe. The number “69” represents the accelerating and decelerating forces in AI, and takes from the center circle of the Korean flag. People may be familiar with this concept as “Eum” (decelerating) and “Yang” (accelerating), where two opposing forces balance each other.
Examples of the Center of Controversies:
Accelerating Force: development in AI technology
Decelerating Force: regulations to mitigate AI risks
The controversies are organized into 8 directions, which take from the outer bars of the Korean flag design. The hope is that this organization will help readers find the areas they are interested in.
1. AI and Individuals
2. AI and Family
3. AI and Businesses
4. AI and Society
5. AI and Economy
6. AI and Government
7. AI and the World
8. AI and the Universe
If the goal of The Last AI was to help people share their ideas with common vocabulary, the goal of this book is to help readers develop their own views and own strategies to prepare the future.
In this sense, this is a book that raises more questions than we can answer.
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The Last AI retweeted
Situations of reaching the Levels 3 or 4 AI Adoption, where AI replaces CEOs or the President, is one of the reasons for writing The Last AI @The_Last_AI.
For a long-term perspective like this, I sometimes wonder if it would be more important to get leaders to read this, like a "report for one" or to get more people to read it to embed the knowledge in our society.
I'll even send a copy if any of the leaders on X (tagged or not tagged) have not read it yet and want to read the book.
Elon Musk
@sama
@DarioAmodei
@demishassabis
@ajassy
@pmarca
@mustafasuleyman
@sundarpichai
@satyanadella
@finkd
Or people not tagged. I guess this post will be more likely be treated as a spam on X and get like 10 views...
For a long-term perspective like this, I sometimes wonder if it would be more important to get leaders to read this, like a "report for one" or to get more people to read it to embed the knowledge in our society.
I'll even send a copy if any of the leaders on X (tagged or not tagged) have not read it yet and want to read the book.
Elon Musk
@sama
@DarioAmodei
@demishassabis
@ajassy
@pmarca
@mustafasuleyman
@sundarpichai
@satyanadella
@finkd
Or people not tagged. I guess this post will be more likely be treated as a spam on X and get like 10 views...
Sam Altman says an AI will be a better CEO of OpenAI than he is, and that he expects it reasonably soon:
"If we had an AI system that could do a better job at making decisions than anyone we could possibly have, be, say, president of the United States, would we, and like r, would we politically or societally want that? It's very unclear. Most people I think today at least would say probably not."
"Or, you know, like an AI CEO of a big company, would you rather have, I think it'd be awesome for OpenAI to have an AI CEO. But I think a lot of people would be like, ah, that's a little scary."
"But I have no delusions that an AI will not be a better CEO of OpenAI than me at some reasonably soon time."
"If that's true, and if some companies or countries don't do that, and others do, and AI is much better, like that will have a real impact in economic competitiveness, national competitiveness, things like that."
"I think people will feel increasingly like, we either do worse, or we put the AI in more and more, influential positions."
"I think people will always want human board members, and that's probably a really great idea."
Read that third quote twice. He is not predicting this for other companies. He is saying it about his own job.
Then look at the pressure he describes right after. Nobody has to be convinced that an AI CEO is a good idea.
If one company hands over the decision and pulls ahead, everyone else picks between falling behind and doing the same. Competitive pressure does the deciding, and what most people would want stops mattering.
His answer to that is human board members. I would take it. I also do not think it is enough on its own.
A board oversees a CEO by reading what it is told, once a quarter. That works because a human CEO can be questioned, and thinks slowly enough for humans to follow along.
What does a board actually check when the thing it oversees makes a thousand consequential calls a day? Nobody has built that. Not for a single AI system anywhere.
- Sam Altman (@sama), CEO of OpenAI, at TreeHacks 2026.
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The Last AI retweeted
Trying to use AGI, which is a technology-centered concept, as a measure for AI adoption, which is more business-oriented concept, in itself causes confusion.
This is the reason for introducing the concepts of the "3 Levels of AI Adoption" and "AI effortlessness. "
The 3 Levels of AI Adoption:
The important milestone equivalent to AGI is "AI Equalization," to reach Level 2 AI Adoption, which is when AI reaches parity for each job humans were carrying out. This way, whereas AGI will be defined by AI "suppliers," Lv2 AI Adoption will be defined by AI "demand," or the users of AI.
Lv3 AI Adoption is when AI takes charge of the whole firms. This concept later became famous by OpenAI's 5 Stages of AI. Anyone wondering about Stages 2 and 4 (AI that innovates) may read about the "enablers" and "the 6 Levels of Autonomous Companies" in the same paper.
AI Effortlessness
We have categorized AI Adoption as either augmentation or automation. However, we may also place both types of AI adoption into the same dimension by measuring how AI reduces human effort. In augmentation, human effort is not reduced completely, while automation can completely eliminate effort. In the dimension of AI Effortlessness, augmentation is expressed as a number between 0 and 1, and automation (replacement automation) is assigned as 1.
This also allows applying of the concepts of "Automated Innovation." In "Advance Automation," where AI Effortlessness is above 1, AI with innovative capabilities would improve on the tasks it was previously carrying out, achieving "innovation" by AI itself.
Whereas people may think automation is just replacing humans, we may think of it as evetually "advancing" the work in some sense. The paper also provides few examples of how these progresses may be meaningful for firms and the economy.
I am excited to hear about this project and hope some of these concepts from my work could be incorporated in the new measure!
Due to X policy, I'll post links in the reply.
This is the reason for introducing the concepts of the "3 Levels of AI Adoption" and "AI effortlessness. "
The 3 Levels of AI Adoption:
The important milestone equivalent to AGI is "AI Equalization," to reach Level 2 AI Adoption, which is when AI reaches parity for each job humans were carrying out. This way, whereas AGI will be defined by AI "suppliers," Lv2 AI Adoption will be defined by AI "demand," or the users of AI.
Lv3 AI Adoption is when AI takes charge of the whole firms. This concept later became famous by OpenAI's 5 Stages of AI. Anyone wondering about Stages 2 and 4 (AI that innovates) may read about the "enablers" and "the 6 Levels of Autonomous Companies" in the same paper.
AI Effortlessness
We have categorized AI Adoption as either augmentation or automation. However, we may also place both types of AI adoption into the same dimension by measuring how AI reduces human effort. In augmentation, human effort is not reduced completely, while automation can completely eliminate effort. In the dimension of AI Effortlessness, augmentation is expressed as a number between 0 and 1, and automation (replacement automation) is assigned as 1.
This also allows applying of the concepts of "Automated Innovation." In "Advance Automation," where AI Effortlessness is above 1, AI with innovative capabilities would improve on the tasks it was previously carrying out, achieving "innovation" by AI itself.
Whereas people may think automation is just replacing humans, we may think of it as evetually "advancing" the work in some sense. The paper also provides few examples of how these progresses may be meaningful for firms and the economy.
I am excited to hear about this project and hope some of these concepts from my work could be incorporated in the new measure!
Due to X policy, I'll post links in the reply.
Defining AGI as AI that can fully automate the economy has some issues:
1. Diffusion. Automation timelines may depend more on diffusion than innovation. For example, it took decades for electricity to diffuse throughout the economy after it was invented.
2. Private Data. Many important economic skillsets are guarded (e.g., TSMC), so it's unclear how or when AI would be given access to learn them.
3. Robotics. Much of the economy is physical (construction, repair, manufacturing), which is a separate and massive challenge.
That is why we defined AGI as human-level AI rather than economy-level AI.
That said, later this month, we'll release a measurement for economy-level AI impacts.
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The Last AI retweeted
To reiterate the 4 Levels of AI Adoption (the AI Pyramid) described in The Last AI:
Level 1: Augmentation
Level 2: Agency
Level 3: Autonomy
Level 4: Authority
For anyone interested in how AI may change our economy and society, check out "The Last AI" (by S. M. sohn)
Level 1: Augmentation
Level 2: Agency
Level 3: Autonomy
Level 4: Authority
For anyone interested in how AI may change our economy and society, check out "The Last AI" (by S. M. sohn)
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The Last AI retweeted
@DeryaTR_the answers are already available, and based on the interviews, Sam Altman appears to have already read "The Last AI," so OpenAI probably knows it as well.
As explained in my article, this 5 Stages of AI is a way to explain to internal stakeholders the "3 Levels of AI Adoption and the 6 Levels of Autonomous Companies."
The Stages 1, 3, 5 correspond to AI Adoption Levels 1,2,3 and Stages 2,4 are "enablers." (One of the reasons some people are confused about Stage 4)
What happens once these levels are achieved is explained in my book "The Last AI" which also introduces the 4 Levels of AI Adoption for society. Once you read it, you will understand why only 4 levels are necessary to get to the last AI.
Links on my profile (due to X policy on links)
As explained in my article, this 5 Stages of AI is a way to explain to internal stakeholders the "3 Levels of AI Adoption and the 6 Levels of Autonomous Companies."
The Stages 1, 3, 5 correspond to AI Adoption Levels 1,2,3 and Stages 2,4 are "enablers." (One of the reasons some people are confused about Stage 4)
What happens once these levels are achieved is explained in my book "The Last AI" which also introduces the 4 Levels of AI Adoption for society. Once you read it, you will understand why only 4 levels are necessary to get to the last AI.
Links on my profile (due to X policy on links)
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"The ultimate form of augmentation is 1-person companies,
while the ultimate form of automation is 0-person companies." (quoting from The Last AI)
papers.ssrn.com/sol3/papers.cf…
Also for anyone interested in this topic, check out this paper on the 3 Levels of AI adoption.
while the ultimate form of automation is 0-person companies." (quoting from The Last AI)
papers.ssrn.com/sol3/papers.cf…
Also for anyone interested in this topic, check out this paper on the 3 Levels of AI adoption.
Zero-person billion dollar companies. Early AGI-like breakthroughs. Viral Sora deepfakes.
Sam Altman broke it all down in our exclusive DevDay conversation.
Highlights:
0:00 Intro
0:43 DevDay's biggest launches
2:13 Agent Builder vs GPT Builder
3:43 The no-code revolution for pool on zero-person companies
6:50 What would 20-year-old Sam build?
10:22 GPT-5 vs Claude on GDPval
11:30 When have we achieved AGI?
12:44 Scientific breakthroughs AI will solve
13:59 AI 'work slop' costs $186/employee
16:12 Sam's viral Sora memes
20:11 Revenue sharing for cameos
22:33 1B jobs are changing
24:35 What work looks like after AGI
25:44 Global AI safety framework
27:46 Most exciting agents to build
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The Last AI retweeted
After reading recent posts about Mathematicians vs Physicists, Physicists vs Economists, Economics vs Finance, etc., here's an observation about Economics vs Business Management on AI Adoption. For those who do not know me, I majored both in Economics and Business so hopefully I am not too biased.
1) Economists have to make assumptions to simplify their analyses. Otherwise, things would become too complicated to model. Because of this, it appears economists tend to be more likely to just pick one side they like and focus more on that side, either on augmentation or automation. For example, an economist can assume AI will advance little, and focus on using AI as a tool, or advance a lot and call it "transformational AI" and begin their anaysis from there.
2) Business management researchers need to go one step further down and give more thoughts to understanding what would advance AI and how it may affect how businesses make decisions inside the firm. An example of this is the Three Levels of AI Adoption for management and the Four Levels of AI Adoption for society. In this framework you need to consider both augmentation and automation and how and why they may transition from one to the other and what may cause friction or resistance to switch.
In short: if Economists find it easier to focus on either augmentation or automation, Management researchers may find it easier to focus on the transition between augmentation and automation.
For More: Differences of perspectives similar to this are abound around us. For anyone interested in how different people may think differently about AI, check out The 69 Controversies of AI adoption. (Links on the next post)
1) Economists have to make assumptions to simplify their analyses. Otherwise, things would become too complicated to model. Because of this, it appears economists tend to be more likely to just pick one side they like and focus more on that side, either on augmentation or automation. For example, an economist can assume AI will advance little, and focus on using AI as a tool, or advance a lot and call it "transformational AI" and begin their anaysis from there.
2) Business management researchers need to go one step further down and give more thoughts to understanding what would advance AI and how it may affect how businesses make decisions inside the firm. An example of this is the Three Levels of AI Adoption for management and the Four Levels of AI Adoption for society. In this framework you need to consider both augmentation and automation and how and why they may transition from one to the other and what may cause friction or resistance to switch.
In short: if Economists find it easier to focus on either augmentation or automation, Management researchers may find it easier to focus on the transition between augmentation and automation.
For More: Differences of perspectives similar to this are abound around us. For anyone interested in how different people may think differently about AI, check out The 69 Controversies of AI adoption. (Links on the next post)
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So,
Level 1 Adoption: Microsoft
Level 3 Adoption: Macrohard
I should call for a Level 2 Adoption firm named
MediumIntermediate
Level 1 Adoption: Microsoft
Level 3 Adoption: Macrohard
I should call for a Level 2 Adoption firm named
MediumIntermediate
Elon Musk just announced Macrohard, a new AI-driven software venture under xAI aimed at simulating companies like Microsoft entirely with artificial intelligence.
He claims that since software giants don't produce physical hardware, their operations from coding to management alone.
xAI has already filed a trademark for Macrohard and is hiring.
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The Last AI retweeted
@sama Yes! The impact of AI adoption in 2 ways.
1) Number of Jobs: As described in The Last AI, more jobs are more likely in AI adoption Levels 1 and 2
2) Nature of Jobs: Jobs using AI may become easier and easier over time, referred to as "effortlessness"
sciencedirect.com/science/articl…
1) Number of Jobs: As described in The Last AI, more jobs are more likely in AI adoption Levels 1 and 2
2) Nature of Jobs: Jobs using AI may become easier and easier over time, referred to as "effortlessness"
sciencedirect.com/science/articl…
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The Last AI retweeted
Help spread the word on AI by asking your local library to get a copy of The 69 Controversies of AI Adoption!
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"where the economy is fundamentally powered by AI"
- for anyone interested, read "The Last AI," the book that introduces AI Economics!
- for anyone interested, read "The Last AI," the book that introduces AI Economics!
OpenAI's Greg Brockman says the AGI future looks less like a monolith - and more like a menagerie of specialized agents. Models that call other models.
“We're heading to a world where the economy is fundamentally powered by AI.”
The goal is to unlock 10x more activity, output, ers the barrier to entry. Domain expertise becomes leverage.
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The Last AI retweeted
@IvankaTrump For people interested in how AI impact our society, read "the 69 Controversies of AI Adoption" by S. M. Sohn!
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So it would be like ArXiv for AI?
AIArXiv?
AIArXiv?
We need a global public repository of Deep Research PDFs. We have a machine that is synthesizing huge amounts of information, insight, and knowledge at a breakneck pace. A person can generate 10 to 15 PhD quality papers per day. There's no sense in duplicating this effort. Plus, if they are published publicly, they can get inducted into other training data sets.
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The Last AI retweeted
Some are excited about the possibility of AGI and ASI bringing prosperity.
Some are afraid of AGI and ASI leading to catastrophe.
What this Book of Controversies is trying to prevent may be the Animal Farm Scenario, where AI may rule over humans.
What is more likely?
Some are afraid of AGI and ASI leading to catastrophe.
What this Book of Controversies is trying to prevent may be the Animal Farm Scenario, where AI may rule over humans.
What is more likely?
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The 69 Controversies of AI Adoption by S. M. Sohn.
Published on 5/25/25.
Link to Amazon: amazon.com/dp/B0F98YFXBF/
Published on 5/25/25.
Link to Amazon: amazon.com/dp/B0F98YFXBF/
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Here is the list of the 69 controversies in the book:
PART 1. INTRODUCTION
Why Are There Controversies?
The Map of the Universe (Taeguk)
The AI Controversy Matrix
The AI Pyramid (The 4 Levels of AI Adoption)
1. The AI Adoption Controversy
PART 2. THE CENTER OF CONTROVERSY
ACCEL)
2. The AGI Definition Controversy
3. The AGI Consciousness Controversy
4. The AGI Development Method Controversy
5. The AI Data Controversy
6. The Time to AGI Controversy
7. The Race to AGI Controversy
8. The AI Open-Source Controversy
9. The Human-Like AI Controversy (The New Turing Test)
10. The Human-Superior AI Controversy (Singularity)
11. The Absolute AI Controversy
CENTER 2 DOWNWARD FORCE (DECEL)
12. The AGI Risk Controversy
13. The Accel vs Decel Controversy
14. The LLM to AGI Controversy
15. The AI Inequality Regulation Controversy
16. The AI Regulation Controversy
17. The AGI Development Prevention Controversy (What = AGI Supply)
18. The AI Adoption Level Limit Controversy (What = AGI Demand)
19. The AI Monopoly Regulation Controversy (Who = Humans)
20. The Level 2 AI Adoption Regulation Controversy (Who = AI)
21. The AGI Containment Controversy (How)
22. The AI Godzilla Controversy
23. The Degree of ASI Superiority Controversy
24. The AI Relative Value System Controversy
25. The Human vs AI Competition Controversy (The Most Important AI Regulation)
PART 3. THE 8 DIRECTIONS OF AI ADOPTION
DIRECTION 1 (SOUTH): AI AND INDIVIDUALS
26. The AI Longevity Controversy
27. The Individual Investor’s AGI Controversy
28. The AI Jobs Controversy (Automation vs Augmentation)
29. The AI vs Profession Controversy
30. The AI Deception / Virtual Reality Controversy
31. The AI Copyright Controversy
DIRECTION 2 (SOUTHWEST): AI AND FAMILY
32. The AI Education Controversy
32–1. The AI Culture Controversy
33. The AI Relationship Controversy
33–1. The AI Birth Rate Controversy
34. The AI Religion Controversy
35. The AI Real Estate Controversy
DIRECTION 3 (SOUTHEAST): AI AND BUSINESS
36. The AI vs Human Individuals Controversy (AI Adoption Level 2)
37. The AI vs Human Organizations Controversy (AI Adoption Level 3)
38. The AI Business Investment Controversy
39. The AI Manipulation Controversy
DIRECTION 4 (WEST): AI AND SOCIETY
40. The AI Crime Controversy
41. The AI Privacy Controversy
42. The AI Bias Controversy
43. The AGI Bias Controversy
DIRECTION 5 (EAST): AI AND ECONOMY
44. The Level 2 AI Economy Controversy (Upheaval of Economic Principles)
45. The Level 3 AI Economics Controversy (Automation vs Augmentation)
45–1. The AI Money Controversy (Economic AI Utopia)
46. The UBI Controversy
47. The AI Ownership Controversy (Inequality of Individuals)
48. The AI Independence Controversy
49. The AI Monopoly Controversy (Inequality of Companies)
DIRECTION 6 (NORTHWEST): AI AND GOVERNMENT
50. The AI in Military Controversy
51. The AI Voting Controversy
52. The AI President Controversy
53. The AI Government Controversy
DIRECTION 7 (NORTHEAST): AI AND THE WORLD
54. The ASI Controllability Controversy
55. The AI Ideology Controversy
56. The AI Ideology Convergence Controversy
57. The AI Country Controversy
58. The AI Dictatorship Controversy
59. The AI Exodus Controversy (Inequality of Countries)
DIRECTION 8 (NORTH): AI AND THE UNIVERSE
60. The ASI Malevolence-Benevolence Controversy
61. The AI vs Humanity Competition Controversy (AI Adoption Level 4)
62. The AI Cybernetics Controversy
63. The AI Existential Risk Controversy
64. The AI Human-First Value Controversy
65. The AI Takeover Controversy
66. The AI-Human War Controversy
67. The AI Multi-Planetary Controversy
68. The Purposes of Humanity and AI Controversy
69. The Last AI Controversy
5/25/25
PART 1. INTRODUCTION
Why Are There Controversies?
The Map of the Universe (Taeguk)
The AI Controversy Matrix
The AI Pyramid (The 4 Levels of AI Adoption)
1. The AI Adoption Controversy
PART 2. THE CENTER OF CONTROVERSY
ACCEL)
2. The AGI Definition Controversy
3. The AGI Consciousness Controversy
4. The AGI Development Method Controversy
5. The AI Data Controversy
6. The Time to AGI Controversy
7. The Race to AGI Controversy
8. The AI Open-Source Controversy
9. The Human-Like AI Controversy (The New Turing Test)
10. The Human-Superior AI Controversy (Singularity)
11. The Absolute AI Controversy
CENTER 2 DOWNWARD FORCE (DECEL)
12. The AGI Risk Controversy
13. The Accel vs Decel Controversy
14. The LLM to AGI Controversy
15. The AI Inequality Regulation Controversy
16. The AI Regulation Controversy
17. The AGI Development Prevention Controversy (What = AGI Supply)
18. The AI Adoption Level Limit Controversy (What = AGI Demand)
19. The AI Monopoly Regulation Controversy (Who = Humans)
20. The Level 2 AI Adoption Regulation Controversy (Who = AI)
21. The AGI Containment Controversy (How)
22. The AI Godzilla Controversy
23. The Degree of ASI Superiority Controversy
24. The AI Relative Value System Controversy
25. The Human vs AI Competition Controversy (The Most Important AI Regulation)
PART 3. THE 8 DIRECTIONS OF AI ADOPTION
DIRECTION 1 (SOUTH): AI AND INDIVIDUALS
26. The AI Longevity Controversy
27. The Individual Investor’s AGI Controversy
28. The AI Jobs Controversy (Automation vs Augmentation)
29. The AI vs Profession Controversy
30. The AI Deception / Virtual Reality Controversy
31. The AI Copyright Controversy
DIRECTION 2 (SOUTHWEST): AI AND FAMILY
32. The AI Education Controversy
32–1. The AI Culture Controversy
33. The AI Relationship Controversy
33–1. The AI Birth Rate Controversy
34. The AI Religion Controversy
35. The AI Real Estate Controversy
DIRECTION 3 (SOUTHEAST): AI AND BUSINESS
36. The AI vs Human Individuals Controversy (AI Adoption Level 2)
37. The AI vs Human Organizations Controversy (AI Adoption Level 3)
38. The AI Business Investment Controversy
39. The AI Manipulation Controversy
DIRECTION 4 (WEST): AI AND SOCIETY
40. The AI Crime Controversy
41. The AI Privacy Controversy
42. The AI Bias Controversy
43. The AGI Bias Controversy
DIRECTION 5 (EAST): AI AND ECONOMY
44. The Level 2 AI Economy Controversy (Upheaval of Economic Principles)
45. The Level 3 AI Economics Controversy (Automation vs Augmentation)
45–1. The AI Money Controversy (Economic AI Utopia)
46. The UBI Controversy
47. The AI Ownership Controversy (Inequality of Individuals)
48. The AI Independence Controversy
49. The AI Monopoly Controversy (Inequality of Companies)
DIRECTION 6 (NORTHWEST): AI AND GOVERNMENT
50. The AI in Military Controversy
51. The AI Voting Controversy
52. The AI President Controversy
53. The AI Government Controversy
DIRECTION 7 (NORTHEAST): AI AND THE WORLD
54. The ASI Controllability Controversy
55. The AI Ideology Controversy
56. The AI Ideology Convergence Controversy
57. The AI Country Controversy
58. The AI Dictatorship Controversy
59. The AI Exodus Controversy (Inequality of Countries)
DIRECTION 8 (NORTH): AI AND THE UNIVERSE
60. The ASI Malevolence-Benevolence Controversy
61. The AI vs Humanity Competition Controversy (AI Adoption Level 4)
62. The AI Cybernetics Controversy
63. The AI Existential Risk Controversy
64. The AI Human-First Value Controversy
65. The AI Takeover Controversy
66. The AI-Human War Controversy
67. The AI Multi-Planetary Controversy
68. The Purposes of Humanity and AI Controversy
69. The Last AI Controversy
5/25/25
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The 69 Controversies of AI Adoption is coming on 5/25/25!
Here is a preview of the first 25 controversies and the 8 Directions of AI Adoption.
---------------------
PART 1. INTRODUCTION
Why Are There Controversies?
The Map of the Universe (Taeguk)
The AI Controversy Matrix
The s of AI Adoption)
1. The AI Adoption Controversy
PART 2. THE CENTER OF CONTROVERSY
CENTER 1 UPWARD FORCE (ACCEL)
2. The AGI Definition Controversy
3. The AGI Consciousness Controversy
4. The AGI Development Method Controversy
5. The AI Data Controversy
6. The Time to AGI Controversy
7. The Race to AGI Controversy
8. The AI Open-Source Controversy
9. The Human-Like AI Controversy (The New Turing Test)
10. The Human-Superior AI Controversy (Singularity)
11. The Absolute AI Controversy
CENTER 2 DOWNWARD FORCE (DECEL)
12. The AGI Risk Controversy
13. The Accel vs Decel Controversy
14. The LLM to AGI Controversy
15. The AI Inequality Regulation Controversy
16. The AI Regulation Controversy
17. The AGI Development Prevention Controversy (What = AGI Supply)
18. The AI Adoption Level Limit Controversy (What = AGI Demand)
19. The AI Monopoly Regulation Controversy (Who = Humans)
20. The Level 2 AI Adoption Regulation Controversy (Who = AI)
21. The AGI Containment Controversy (How)
22. The AI Godzilla Controversy
23. The Degree of ASI Superiority Controversy
24. The AI Relative Value System Controversy
25. The Human vs AI Competition Controversy (The Most Important AI Regulation)
PART 3. THE 8 DIRECTIONS OF AI ADOPTION
DIRECTION 1 (SOUTH): AI AND INDIVIDUALS
DIRECTION 2 (SOUTHWEST): AI AND FAMILY
DIRECTION 3 (SOUTHEAST): AI AND BUSINESS
DIRECTION 4 (WEST): AI AND SOCIETY
DIRECTION 5 (EAST): AI AND ECONOMY
DIRECTION 6 (NORTHWEST): AI AND GOVERNMENT
DIRECTION 7 (NORTHEAST): AI AND THE WORLD
DIRECTION 8 (NORTH): AI AND THE UNIVERSE
PART 4. TOWARDS THE ART OF AI STRATEGY
Link to pre-order on the next post.
Here is a preview of the first 25 controversies and the 8 Directions of AI Adoption.
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PART 1. INTRODUCTION
Why Are There Controversies?
The Map of the Universe (Taeguk)
The AI Controversy Matrix
The s of AI Adoption)
1. The AI Adoption Controversy
PART 2. THE CENTER OF CONTROVERSY
CENTER 1 UPWARD FORCE (ACCEL)
2. The AGI Definition Controversy
3. The AGI Consciousness Controversy
4. The AGI Development Method Controversy
5. The AI Data Controversy
6. The Time to AGI Controversy
7. The Race to AGI Controversy
8. The AI Open-Source Controversy
9. The Human-Like AI Controversy (The New Turing Test)
10. The Human-Superior AI Controversy (Singularity)
11. The Absolute AI Controversy
CENTER 2 DOWNWARD FORCE (DECEL)
12. The AGI Risk Controversy
13. The Accel vs Decel Controversy
14. The LLM to AGI Controversy
15. The AI Inequality Regulation Controversy
16. The AI Regulation Controversy
17. The AGI Development Prevention Controversy (What = AGI Supply)
18. The AI Adoption Level Limit Controversy (What = AGI Demand)
19. The AI Monopoly Regulation Controversy (Who = Humans)
20. The Level 2 AI Adoption Regulation Controversy (Who = AI)
21. The AGI Containment Controversy (How)
22. The AI Godzilla Controversy
23. The Degree of ASI Superiority Controversy
24. The AI Relative Value System Controversy
25. The Human vs AI Competition Controversy (The Most Important AI Regulation)
PART 3. THE 8 DIRECTIONS OF AI ADOPTION
DIRECTION 1 (SOUTH): AI AND INDIVIDUALS
DIRECTION 2 (SOUTHWEST): AI AND FAMILY
DIRECTION 3 (SOUTHEAST): AI AND BUSINESS
DIRECTION 4 (WEST): AI AND SOCIETY
DIRECTION 5 (EAST): AI AND ECONOMY
DIRECTION 6 (NORTHWEST): AI AND GOVERNMENT
DIRECTION 7 (NORTHEAST): AI AND THE WORLD
DIRECTION 8 (NORTH): AI AND THE UNIVERSE
PART 4. TOWARDS THE ART OF AI STRATEGY
Link to pre-order on the next post.
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